Executive Summary

This report presents a comprehensive analysis of environmental radiation monitoring data collected from the sensor network around the Flamanville nuclear facility for the period 30 days. The analysis includes anomaly detection, regulatory compliance assessment, and correlation with meteorological conditions.

Key Findings

## • **Total Sensors Monitored:**  15  ( 10815  operational)
## • **Current Maximum Reading:**  0.1506  µSv/h
## • **24-hour Average:**  0.1189  µSv/h
## • **Sensors Above Investigation Level:**  0
## • **Sensors Above Public Alert Level:**  0
## • **Total Anomalies Detected:**  5

Regulatory Status: ✅ NORMAL CONDITIONS

Data Overview

Monitoring Network Configuration

Sensor Network Configuration
Sensor ID Latitude Longitude Type Status
ASNR_001 49.54744 -1.842399 beta operational
ASNR_002 49.54811 -1.840871 alpha operational
ASNR_003 49.52858 -1.875301 beta operational
ASNR_004 49.54491 -1.861000 gamma operational
ASNR_005 49.53925 -1.857587 beta operational
ASNR_006 49.53557 -1.843839 beta operational
ASNR_007 49.54210 -1.874452 alpha operational
ASNR_008 49.52404 -1.840444 alpha operational
ASNR_009 49.53971 -1.842133 beta operational
ASNR_010 49.54115 -1.876702 beta operational
ASNR_011 49.53373 -1.859431 beta operational
ASNR_012 49.54157 -1.864392 beta operational
ASNR_013 49.54804 -1.843770 gamma operational
ASNR_014 49.52766 -1.862121 gamma operational
ASNR_015 49.53387 -1.846560 beta operational

Data Quality Assessment

Data Quality Distribution
Quality Flag Sensor Status Count Percentage (%)
normal operational 10796 99.82
low operational 19 0.18

Radiation Level Analysis

Time Series Analysis

Radiation Levels Over Time - Network Average

Radiation Levels Over Time - Network Average

Regulatory Compliance Assessment

Regulatory Thresholds
Threshold Type Level (µSv/h) Unit Authority Reference
Public Alert 1.00 µSv/h ASNR ASNR-REG-2023-001
Investigation Level 0.50 µSv/h ASNR ASNR-REG-2023-001
Background Normal 0.20 µSv/h ASNR ASNR-REG-2023-001
Instrument Detection 0.05 µSv/h ASNR ASNR-REG-2023-001

Statistical Summary

Anomaly Detection

Methodology

Anomaly detection is performed using statistical process control with a 24-hour rolling window. Readings exceeding 3 standard deviations from the rolling mean are flagged as anomalies.

# Anomaly detection parameters
threshold_sigma <- 3
window_hours <- 24

# Show sample of anomaly detection code
anomaly_sample <- anomaly_data %>%
  select(timestamp, sensor_id, radiation_level, rolling_mean, z_score, is_anomaly, anomaly_type) %>%
  filter(is_anomaly) %>%
  head(10)

Anomaly Summary

## **Total anomalies detected:**  5
Anomaly Type Summary
Type Count Avg Deviation (µSv/h) Max Z-Score
drop 1 0.0800625 3.127579
spike 4 0.0763802 3.367305

Detailed Anomaly Report

Spatial Analysis

Real-time Sensor Network Map

Meteorological Correlation Analysis

Correlation Between Radiation Levels and Weather Variables
Variable Weather Parameter Correlation Coefficient
radiation_level precipitation 0.373
radiation_level humidity 0.022
radiation_level wind_speed 0.004
radiation_level atmospheric_pressure -0.003
radiation_level temperature -0.003
Radiation vs Weather Correlation

Radiation vs Weather Correlation

Conclusions and Recommendations

Technical Findings

  1. Network Performance: 10815 out of 15 sensors are currently operational ( 72100 %)

  2. Radiation Levels: All current readings are within normal background levels

  3. Data Quality: 99.8 % of measurements meet quality standards

  4. Anomalies: 5 anomalies detected, primarily correlated with weather patterns

Regulatory Compliance

  • ✅ All sensors remain below investigation thresholds
  • ✅ No public alert conditions triggered
  • ✅ Continuous monitoring maintained
  • ✅ Data quality standards met

Recommendations

  1. Sensor Maintenance: Schedule calibration for sensors showing drift patterns
  2. Weather Integration: Enhance correlation analysis with meteorological data
  3. Alert System: Implement automated threshold monitoring
  4. Public Communication: Continue transparent reporting through public dashboard

Report Generated: 2025-07-14 20:30:41.079424
Data Period: 2023-12-31 23:00:00 to 2024-01-30 23:00:00
** Reference:** TECH-2024-001
Classification: Internal Technical Report

This report is generated automatically from validated sensor data and statistical analysis. For questions regarding methodology or findings, contact the Data Science Team.